Principles of fair assessment guidance for academic staff

Addressing student workload inconsistencies: design and implementation of a principles of fair assessment guide for academic staff

This short article reflects on work undertaken as School Director of Teaching and Learning in the School of Archaeology, Geography and Environmental Science at the University of Reading in designing and implementing a new principles of fair assessment guidance document for staff.

As is common in the discipline, a varied range of assessment types are deployed within my School, including multiple choice tests, laboratory technical reports, field reports, field notebooks, essays, exams (seen and unseen), reflective diaries/blogs, screencasts, individual and group presentations, and collaborative group-based reports and Wikis. External examiners confirm that assessments are appropriately designed to assess whether a student has achieved the intended learning objectives (Biggs, 1999; Bloxham and Boyd, 2007) and form an integral part of the module design. Our approach to module and assessment design is also consistent with the outcomes-based approach adopted within credit frameworks (Tam, 2014; Gosling and Moon, 2001) and is representative of the paradigm shift in higher education from the traditional testing of knowledge, and the instructive view of learning, to a more student-centred approach to learning (Howell, 2011).

Analysis of student feedback from module and programme evaluations demonstrates that innovative assessment is often highly motivational and well regarded by students. Furthermore, students often appreciate the importance of skills development for future personal, academic and professional development (Fern et al, 2010; Fahnert, 2015).  However, our student feedback also indicated a perception of unfairness in workload expectations between modules of the same credit weighting and level of study. Subsequent review of assessment regimes confirmed variation, with some modules including four or five quite substantial assignments in the summative assessment, while others were far lighter in comparison. This potentially causes inconsistencies in workload for students (and staff) depending on their chosen pathway and some students admitted to sometimes choosing modules based on perceived workload rather than academic interest or benefit.

We reflected on the extent to which this may be a real problem from the point of view of effective assessment of student achievement of intended learning outcomes, particularly given the outcomes-based approach in use (Tam, 2014; Gosling and Moon, 2001). The University itself did not have an institutional policy on the weighting of assessment required per module credit.  However, discussion in the literature has looked at the impact of assessment weighting on academic performance (e.g. Cohall and Skeete, 2014) and some Universities do use assessment-weight to credit-value look-up tables or similar.

My conclusion was that providing guidance to colleagues on what might be a ‘typical’ assessment load for the equivalent of a 10-credut module would be beneficial to ensure “accuracy, fairness and consistency” (Butcher et al, 2006, p.96). Discussions with staff had revealed a wish to have more guidance on setting an appropriate amount of assessment, such as word limits and how alternative assessments may compare with workload for essays, reports and exams, which were traditionally used in this discipline. I therefore produced the Principles of Fair Assessment guidance (appendix 1) as a single tangible document that could be easily shared electronically and be used by colleagues as a simple reference point when designing module content and assessment.

This guidance document is in two parts, with the first section setting out our expectations for “fair” assessment practices, including in respect of inclusive assessment design, fair workload, robust marking and scrutiny processes, timely and developmental feedback, and appropriate identification and management of academic misconduct. The second section provides example assessment and their associated weighting mapped to a 10-credit module, whilst recognising some differences will occur and may be necessary. The key principles have been adapted from the indicators of sound practice published in the QAA Quality Code Chapter B6: assessment of students (QAA, 2013). This Chapter provides a reasonably common-sense approach to how providers can meet expectations for maintaining and enhancing quality in this area. The second part, setting out weightings for different assessment types, is adapted from Galvin, et al. (2012), following a desk-based review of policies at a range of Universities and other higher education providers. The guidance does not currently advise on how many assessments should be set, just the overall assessment weighting. Galvez-Bravo (2016) recently explored the relationship between student achievement and number of assessments and found no relationship between fewer assessments and improved academic performance.  Indeed, she found a slight trend showing the opposite (Galvez-Bravo, 2016).

Discussion of the draft document confirmed student representative support for the approach and the document is now actively used as a reference point within the School of Archaeology, Geography and Environmental Science, and more widely within the University. The guidance has resulted in improved consistency in student workload cross-School on different module pathways and helped to remove obvious examples of “over-assessment”. The work presented here is intended to contribute to discussions in other University departments where the optimum balance of teaching, learning and assessment continues to be sought to enhance the student experience while maintaining rigorous academic standards.

Principles of Fair Assessment

Assessments should assess what the students have been required to learn.

  • Assessment is linked to the learning that students undertake on the course including directed self-study.

The student workload should be appropriate

  • The volume, timing and nature of assessment enable students to demonstrate the extent to which they have achieved the intended learning outcomes.
  • Workloads for students on the same programme should be broadly similar, even where they are taking different modules as part of that programme.

Disabilities must be catered for

  • Through inclusive design wherever possible, and through individual reasonable adjustments wherever required, assessment tasks provide every student with an equal opportunity to demonstrate their achievement.

Marking processes are robust and subject to external scrutiny

  • Processes for marking assessments and for moderating marks are clearly articulated and consistently operated by those involved in the assessment process.
  • Marking consistency is checked by external examiners and through internal moderation. Where appropriate (e.g. dissertations) double blind marking is undertaken.
  • Examination Boards apply fairly and consistently regulations for progression within programmes and for the award of credits and qualifications.

Feedback on assessment is timely, constructive and developmental

  • Feedback will be appropriate to the nature of the assessment task.
  • Feedback will be given in ways that promote students’ learning.
  • Feedback will be relevant, informative and fit for purpose.
  • Feedback will be provided within 15 working days of submission unless subject to special exemption (e.g. dissertations)

Academic misconduct is taken seriously and investigated fairly

  • Processes for preventing, identifying, investigating and responding to unacceptable academic practice (including plagiarism) are understood by all staff.
  • Students are provided with opportunities to develop an understanding of, and the necessary skills to demonstrate, good academic practice.

Students have access to the University’s Appeal procedures

  • In addition to the formal process, support is available from RUSU advisors and concerns can be discussed informally with Personal tutors or more formally with the School Director of Teaching and Learning.

Module Assessment Weighting Guidance

The programme director and SDTL should have sufficient oversight of module assessment design and weighting to ensure compatibility with the SAGES Principles of Fair Assessment guidance, and in particular that the student workload should be appropriate:

  • The volume, timing and nature of assessment enable students to demonstrate the extent to which they have achieved the intended learning outcomes.
  • Workloads for students on the same programme should be broadly similar, even where they are taking different modules as part of that programme.

As not all assessment items will be essay or exam based, broad equivalences for other means of assessment should be applied in achieving the total essay word requirements. In establishing relativities between different styles of assessment consideration may be given to:

  1. the complexity of the assignment; 
  2. the estimated amount of time required to think about, sort and structure the response;
  3. the proportion of the response that will require creative, reflective, analytical thought and evidence of deep learning that is not able to be routinely drawn from texts and lecture notes.

Suggested equivalences[1] are presented below. These guidelines may vary according to the three criteria above. Module convenors should review and adjust assessment loads to ensure the total module load falls within the range 0.8 to 1.2.

AssessmentLengthWeight (10 credit module)
Book Review8000.2
Short Oral Presentation5 mins0.2
Seminar Paper10000.2
Exam2 hr1
Project/short dissertation30001
Group Presentatione.g. 10 mins/member0.2
Reflective Journal or Learning Log2000-25000.3
Group Report750/member0.3
Practical/Field Report15000.5
Field/Lab Notebook0.2

[1] based on sector analysis by Galvin, A. et al (2012) Assessment Workload and Equivalences, University College Dublin.

British and Chinese students

China field class 2019

I was pleased to participate on the first University of Reading Environmental Science undergraduate field class to Nanjing University of Information Science and Technology (NUIST), organised by my colleagues Steve Robinson and Hong Yang. A group of Reading third year students joined 36 Chinese students studying our Environmental Science programme at the Reading-NUIST Academy at NUIST for 10 days of activities. Further details about the field class and our partnership with NUIST can be found here.

My existing close links with NUIST started in 2011 and I regularly publish journal articles with my collaborator Professor Defu Xu. It was great to meet up with him and other colleagues again in China during the field class.

field class in Nanjing
British and Chinese students
British and Chinese students
British and Chinese students
Panda at Taihu Lake National Wetland Park
Panda at Taihu Lake National Wetland Park